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Questions tagged [mlops]

This tag is for programming questions about MLOps, which is the application of DevOps principles in the design and deployment of Machine Learning (ML) systems.

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Related tags

  • mlflow
  • kubeflow
  • feature-store
228 questions
11
votes
4 answers

Setting-up MLflow on Google Colab

I frequently use Google Colab to train TF/PyTorch models as Colab provides me with GPU/TPU runtime. Besides, I like working with MLflow to store and compare trained models, tracking progress, sharing, etc. What are the available solutions to use…
SvitlanaGA...supportsUkraine
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7
votes
3 answers

MLFlow tracking ui not showing experiments on local machine (laptop)

I am a beginner in mlflow and was trying to set it up locally using Anaconda 3. I have created a new environment in anaconda and install mlflow and sklearn in it. Now I am using jupyter notebook to run my sample code for mlflow. ''' import os import…
Swapnil
  • 73
  • 1
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7
votes
1 answer

Is it necessary to commit DVC files from our CI pipelines?

DVC uses git commits to save the experiments and navigate between experiments. Is it possible to avoid making auto-commits in CI/CD (to save data artifacts after dvc repro in CI/CD side).
B.P.Puneeth Pai
  • 87
  • 6
6
votes
1 answer

MlflowException: API request (Caused by ResponseError('too many 503 error responses'))

I am using mlflow to register my model. I try to use 'Scenario 4' when artifacts load to S3 bucket from local. Add credentials of S3 bucket to .aws/credentials Set endpoint and mlflow…
sergzemsk
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6
votes
1 answer

Vertex AI pipelines import custom modules

I'm developing a complex pipeline in Vertex AI using Pipelines and components. I would like to import some custom modules and functions I developed for this use case. Unfortunately, I cannot figure out how to import those custom functions in my code…
Andrea Cola
  • 127
  • 1
  • 8
5
votes
2 answers

Amazon SageMaker Model Registry / Pipelines - how to manually set a Stage for a given Model Version?

This might be a very specific question, but I will try anyway. I want to explicitly set the Stage column in Model registry for a given Model Version: This picture comes from the documentation and it gets set only when you run the example SageMaker…
blahblah
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  • 2
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  • 30
4
votes
1 answer

Access Parameter's value directly in AWS Sagemaker Pipeline

Inside a function that returns a Pipeline, where a Parameter is defined, e.g. (taken from here) def get_pipeline(...): foo = ParameterString( name="Foo", default_value="foo" ) # pipeline's steps definition here step =…
uarfr
  • 43
  • 5
4
votes
0 answers

Convert/wrap Spacy model into a Tensorflow model

Is it possible to convert a saved spacy model into a TensorFlow model? Spacy provides a wrapper to work with TensorFlow models. Mentioned here. Can this be done the other way around? I need to convert a Spacy model into a TensorFlow model or wrap it…
Shashank Yadav
  • 174
  • 1
  • 11
4
votes
0 answers

Is there mlflow REST api to hard delete experiments, runs?

Mlfow exp delete api does soft delete and when you create experiment with that name, it gives error RESOURCE_ALREADY_EXISTS. Is there any way to delete experiment permanently through…
veeresh patil
  • 1,168
  • 1
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  • 18
4
votes
3 answers

How can I save more metadata on an MLFlow model

I am trying to save a model to MLFlow, but as I have a custom prediction pipeline to retrieve data, I need to save extra metadata into the model. I tried using my custom signature class, which It does the job correctly and saves the model with the…
Angelo
  • 575
  • 3
  • 18
4
votes
2 answers

Setup Mlflow backend (SQLite) and artifact (Azure Blob Storage) stores

I would like to setup Mlflow to have the following components : Backend store (local) : using a SQLite database locally to store Mlflow entities (run_id, params, metrics...) Artifact store (remote) : using a blob storage on my Azure Data Lake…
Downforu
  • 317
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  • 13
4
votes
1 answer

Use mlflow to serve a custom python model for scoring

I am using Python code generated from an ML software with mlflow to read a data frame, perform some table operations and output a data frame. I am able to run the code successfully and save the new data frame as an artifact. However, I am unable to…
Subhojyoti Lahiri
  • 109
  • 3
  • 10
3
votes
1 answer

How do I save a yolov5 model among the registered models in MLflow and then load it either directly or from weights (.pt) to make predictions?

My objective is to : save the yolov5 model in MLflow Model Registry Load the model directly from model registry so that we can make predictions. Have access to the results of prediction (bounding boxes). Current steps followed: Cloned the yolov5…
atharva parikh
  • 41
  • 3
3
votes
1 answer

Not able to update experiment metrics from iterative.ai studio

I have DVC and gitlab-ci integrated using CML and with studio as well. But whenever I run an experiment from studio dashboard, the new experiment appears on the dashboard but metrics don't get updated in git and thus in studio dashboard as well. But…
Shabbir Bawaji
  • 115
  • 1
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3
votes
1 answer

Deploying a new model to a sagemaker endpoint without updating the config?

I want to deploy a new model to an existing AWS SageMaker endpoint. The model is trained by a different pipeline and stored as a mode.tar.gz in S3. The sagemaker endpoint config is pointing to this as the model data URL. Sagemaker however doesn't…
Steffenk
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1
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